Low back pain is one of the most common and disabling musculoskeletal disorders worldwide and the third most common reason for surgery in the United States. The lower back, or lumbar region, supports most of the body's weight; it controls spinal movement and stability through the interaction between bones, nerves, muscles, ligaments, and fascia within the lumbar region. Any disorder of those tissues could cause low back pain (LBP); emerging evidence indicates that the thoracolumbar fascia (TLF) is the lower back's most pain-sensitive soft tissue structure. TLF consists of dense connective tissue separated by loose connective tissue, allowing TLF layers to pass easily during torso movement. A series of foundational studies found that patients enduring long-term low back pain have different TLF structures than those without LBP. Injuries may result in adhesions and fibrosis, which may cause adjacent dense connective tissue layers to lose independent motion, limiting movement and causing pain. LBP is diagnosed by investigating the patient's medical history to identify symptoms and then examining the patient to determine the cause of the pain.
If the pain persists after diagnosis and treatment, further investigation is required; an ultrasound scan is used as the next step. Ultrasound (US) imaging is a non-invasive and instantaneous method to evaluate soft, connective tissue structures such as muscles, tendons, ligaments, and fascia. Even though measuring echo intensity helps evaluate the soft tissues, this method still has limitations in diagnosing LBP; 90 % of all LBP patients are diagnosed with non-specific LBP, referred to as pain with no definitive cause . An in-depth investigation of US images could potentially provide more specificity in identifying sources of LBP. By providing information about soft tissue structure, texture analysis could increase US images' diagnostic power. The texture of an ultrasound image is the variation of pixel intensities throughout the region of interest (ROI) that produces different patterns; texture analysis is an approach that quantifies the characteristic variation of pixel intensities within ROI to describe tissue morphological characteristics. First-order texture analysis, second-order texture analysis, and grey-level run length texture analysis are types of analysis that could be applied to quantify parameters that describe the features of the texture; the grey-level analysis is usually conducted in four directions of the texture. This study has four objectives; the first objective is to use first-order and second-order analysis to determine texture parameters and determine whether those parameters can differentiate between individuals with and without LBP. The second objective is to use grey level run length analysis to quantify texture parameters in four directions (0^°,45^°,90^°,135^°) and examine whether those parameters can differentiate between individuals with and without LBP. The third objective is to determine the correlation between the first, second, and run length parameters. The fourth objective is to explore how first-order, second order and grey level run length parameters are affected by US machine settings. A custom-written MATLAB program was developed to quantify first and second-order texture parameters and grey-level run length parameters. Using JMP software, each parameter was statistically compared between individuals with and without LBP. Among nine first- and second-order texture parameters, four showed statistically significant differences between individuals with and without LBP. Among 44 run-length parameters, 9 showed statistically significant differences between individuals with and without LBP. The current study also revealed some strong correlations between first, second, and run length parameters; it also shows that the US machine setting has minor effects on the three types of parameters. Although the present study was conducted on a relatively small sample size, the results indicate that one direction of grey level run length analysis and first and second-order texture analysis can differentiate between people with and without LBP. / Master of Science / Low back pain (LBP) is one of the most common and disabling musculoskeletal disorders worldwide and the third most common reason for surgery in the United States. Due to LBP's effect on mobility, it is one of the leading causes of absence from work, early retirement, and long-term disability payments. The thoracolumbar fascia (TLF), a connective tissue that stabilizes the trunk, pelvis, and spine, is considered the most sensitive tissue to LBP. LBP diagnosis is based on the patient's medical history to identify symptoms and then on an examination to determine the cause. If the pain persists after diagnosis and treatment, imaging is recommended as the next step. Ultrasound (US) imaging produces a cross-sectional image of the structure and has been used to compare TLF structure in people with and without LBP. Additional analyses must be done to increase US images' ability to diagnose LBP. In the current project, three types of analysis of US images were performed; first-order, second-order, and grey level run length analyses were performed to determine parameters for the images of the two groups of people; selected parameters were noted to distinguish between people with and without LBP.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/115666 |
| Date | 06 July 2023 |
| Creators | Al Khafaji, Ghaidaa Ghanim |
| Contributors | Department of Biomedical Engineering and Mechanics, Wang, Vincent M., Kozar, Albert John, Han, Aiguo |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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